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Item type:Publication, Access status: with files , Efficient Chebyshev reconstruction for the anisotropic equilibrium model in magnetic particle imaging(Institute of Physics (IOP), 2026-10-15); ; ; ; Objective. Magnetic particle imaging (MPI) is a tomographic imaging modality capable of real-time, high-sensitivity mapping of superparamagnetic iron oxide nanoparticles. Model-based image reconstruction provides an alternative to conventional methods that rely on a measured system matrix, eliminating the need for laborious calibration measurements. Nevertheless, model-based approaches must account for the complexities of the imaging chain to maintain high image quality. This work investigates and accelerates an adapted direct Chebyshev reconstruction (DCR) method that accounts for the physical effect of magnetic nanoparticle anisotropy. Approach. The adapted DCR method employs weighted Chebyshev polynomials in the frequency domain and incorporates a spatially variant deconvolution step to compensate for magnetic anisotropy effects. The method is evaluated on five experimental phantoms and compared with model-based and measured system matrix reconstructions. In addition, an efficient approximation of the spatially variant deconvolution is introduced to reduce computational runtime and memory consumption while maintaining reconstruction accuracy. The proposed approach is further investigated on simulated three-dimensional data to assess its scalability to volumetric MPI. Main results. The adapted DCR method significantly improves reconstruction quality in real measurements and achieves image fidelity comparable to that of the measured system matrix reconstruction and superior to that of the model-based system matrix reconstruction. The proposed approximation of the spatially variant deconvolution preserves the reconstruction accuracy while reducing computational and memory requirements. Its computational complexity is reduced to 𝓞 (𝘕log𝘕). The method also successfully reconstructs simulated 3D data, demonstrating its applicability to volumetric MPI. Significance. The results demonstrate the potential of the adapted DCR approach to improve model-based MPI reconstruction while avoiding the need for a system matrix. The efficient deconvolution approximation makes the method particularly attractive for high-resolution and three-dimensional imaging by substantially improving its computational efficiency and scalability.Publicationtype: Journal Article7 4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Deep learning for restoring MPI system matrices using simulated training data(IOP Publishing, 2026-05-13); ; ; ; Objective. Magnetic particle imaging reconstructs tracer distributions using a system matrix (SM) obtained through time-consuming, noise-prone calibration measurements. Methods for addressing imperfections in measured system matrices increasingly rely on deep neural networks, yet curated training data remain scarce. This study evaluates whether physics-based simulated system matrices can be used to train deep learning (DL) models for different SM restoration tasks, i.e. denoising, accelerated calibration, upsampling, and inpainting, that generalize to measured data. Approach. A large dataset of system matrices was generated using an equilibrium magnetization model extended with uniaxial anisotropy. The dataset spans particle, scanner, and calibration parameters for 2D and 3D trajectories, and includes background noise injected from empty-frame measurements. For each restoration task, DL models were compared with classical non-learning baseline methods. Quantitative performance was evaluated on simulated data using peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). For measured data, performance was assessed qualitatively by visual comparison of system matrices and the resulting reconstructions. Main results. The models trained solely on simulated system matrices generalized to measured data across all tasks: for denoising, DnCNN/RDN/SwinIR outperformed discrete cosine transform and soft thresholding baseline by dB PSNR and up to +0.1 SSIM on simulations and led to perceptually better reconstructions of real data; for 2D upsampling, SMRnet exceeded bicubic by ∼ 20 dB PSNR and ∼ 0.08 SSIM at ×2–×4 but these gains did not transfer qualitatively to real measurements. For 3D accelerated calibration, SMRnet matched tricubic in noiseless cases and was more robust under noise, and for 3D inpainting, biharmonic inpainting was superior when noise-free but degraded with noise, while a PConvUNet maintained quality and yielded less blurry reconstructions. Significance. The demonstrated transferability of DL models trained on simulations to real measurements mitigates the data-scarcity problem, which intensifies with model scale. This enables the development of new methods beyond current measurement capabilities and supports pre-training of large models on simulated data.Publicationtype: Journal Article38 47 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A procedure for accurate dose measurement in radiotherapy research at millimetre-sized synchrotron beams(IOP Publishing, 2025-11-12); ; ; ; Objective.Synchrotron-based spatially fractionated radiotherapy and ultra-high dose rate (UHDR) radiotherapy have been shown to better spare healthy tissue function in comparison to conventional radiotherapy, while controlling the tumour with the same efficacy. In recent years, an increasing amount of research has been carried out in these fields with promising results. However, further experiments remain essential, since the underlying mechanisms of healthy tissue preservation are not yet fully understood. The characterisation of synchrotron beamlines at the Deutsches Elektronen-Synchrotron in Hamburg represents an opportunity to increase the number of sites where pre-clinical studies could be conducted in the future. However, the beams available at this synchrotron are only a few millimetres in size and measuring absorbed dose with established detectors and dosimetry protocols represents a challenge.Approach.We show a procedure to accurately determine the beam dose rate under such conditions by first characterising a monochromatic beamline. After validation, and with the support of Monte Carlo simulations, the procedure is adapted to investigate a white-beam beamline, at which photon flux and mean energy can be varied with Cu absorbers.Main results.With the developed procedure, it is possible to measure absorbed dose at these beamlines with relative uncertainties below 10%. In particular, at the white-beam beamline, the dose rate varies between about 20 Gy s-1and about 1800 Gy s-1, thus offering the opportunity to carry out much-needed systematic studies. Moreover, pilot experiments with a mouse phantom demonstrate that it is possible to treat small animals with such small-sized beams by using dose-painting techniques, with an agreement between prescribed and delivered dose within ±15%.Significance. This work represents a first step towards the implementation of reproducible pre-clinical studies at the PETRA III synchrotron, further contributing to a transition of spatially-fractionated and UHDR radiotherapy techniques into clinical practice.Publicationtype: Journal Article36 11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Analysis of leakage artifacts and their impact on convergence of algebraic reconstruction in multi-contrast magnetic particle imagingObjective. Magnetic particle imaging (MPI) is a tracer-based medical imaging modality with great potential due to its high sensitivity, high spatiotemporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which the use of regularization methods can address. Multi-contrast MPI reconstructs the signal from different tracer materials or environments separately, resulting in multi-channel images that enable quantification of, for example, temperature or viscosity. Single- and multi-contrast MPI reconstructions produce different kinds of artifacts. The objective of this work is threefold: first, to present the concept of multi-contrast specific MPI channel leakage artifacts; second, to ascertain the source of these leakage artifacts; and third, to introduce a method for their reduction. Approach. A definition for leakage artifacts is established, and a quantification method is proposed. A comprehensive analysis is conducted to establish a connection between the properties of the multi-contrast MPI system matrix and the leakage artifacts. Moreover, a two-step measurement and reconstruction method is introduced to reduce channel leakage artifacts between multi-contrast MPI channels. Main results. The severity of these artifacts correlates with the system matrix shape and condition number and depends on the similarity of the corresponding frequency components. Using the proposed two-step method on both semi-simulated and measured data a significant leakage reduction and speed up the convergence of the multi-contrast MPI reconstruction was observed. Significance. The multi-contrast system matrix analysis we conducted is essential for understanding the source of the channel leakage artifacts and finding methods to reduce them. Our proposed two-step method is expected to improve the potential for real-time multi-contrast MPI applications.Publicationtype: Journal Article5 30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Characterization of the clinically approved MRI tracer resotran for magnetic particle imaging in a comparison study(IOP Publishing, 2024-07-01); ; ; ; Objective. The availability of magnetic nanoparticles (MNPs) with medical approval for human intervention is fundamental to the clinical translation of magnetic particle imaging (MPI). In this work, we thoroughly evaluate and compare the magnetic properties of an magnetic resonance imaging (MRI) approved tracer to validate its performance for MPI in future human trials. Approach. We analyze whether the recently approved MRI tracer Resotran is suitable for MPI. In addition, we compare Resotran with the previously approved and extensively studied tracer Resovist, with Ferrotran, which is currently in a clinical phase III study, and with the tailored MPI tracer Perimag. Main results. Initial magnetic particle spectroscopy (MPS) measurements indicate that Resotran exhibits performance characteristics akin to Resovist, but below Perimag. We provide data on four different tracers using dynamic light scattering, transmission electron microscopy, vibrating sample magnetometry measurements, MPS to derive hysteresis, point spread functions, and a serial dilution, as well as system matrix based MPI measurements on a preclinical scanner (Bruker 25/20 FF), including reconstructed images. Significance. Numerous approved MNPs used as tracers in MRI lack the necessary magnetic properties essential for robust signal generation in MPI. The process of obtaining medical approval for dedicated MPI tracers optimized for signal performance is an arduous and costly endeavor, often only justifiable for companies with a well-defined clinical business case. Resotran is an approved tracer that has become available in Europe for MRI. In this work, we study the eligibility of Resotran for MPI in an effort to pave the way for human MPI trials.Publicationtype: Journal Article12 26 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Solving the MPI reconstruction problem with automatically tuned regularization parameters(2024-02-21); ; In the field of medical imaging, magnetic particle imaging (MPI) poses a promising non-ionizing tomographic technique with high spatial and temporal resolution. In MPI, iterative solvers are used to reconstruct the particle distribution out of the measured voltage signal based on a system matrix. The amount of regularization needed to reconstruct an image of good quality differs from measurement to measurement, depending on the MPI system and the measurement settings. Finding the right choice for the three major parameters controlling the regularization is commonly done by hand and requires time and experience. In this work, we study the reduction to a single regularization parameter and propose a method that enables automatic reconstruction. The method is qualitatively and quantitatively validated on several MPI data sets showing promising results.Publicationtype: Journal Article3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Saline bolus for negative contrast perfusion imaging in magnetic particle imaging(IOP Publishing, 2023-09-07); ; ; ; Objective. Magnetic particle imaging (MPI) is capable of high temporal resolution measurements of the spatial distribution of magnetic nanoparticles and therefore well suited for perfusion imaging, which is an important tool in medical diagnosis. Perfusion imaging in MPI usually requires a fresh bolus of tracer material to capture the key signal dynamics. Here, we propose a method to decouple the imaging sequence from the injection of additional tracer material, without further increasing the administered iron dose in the body with each image. Approach. A bolus of physiological saline solution without any particles (negative contrast) diminishes the steady-state concentration of a long-circulating tracer during passage. This depression in the measured concentration contributes to the required contrast dynamics. The presence of a long-circulating tracer is therefore a prerequisite to obtain the negative contrast. As a quantitative tracer based imaging method, the signal is linear in the tracer concentration for any location that contains nanoparticles and zero in the surrounding tissue which does not provide any intrinsic signal. After tracer injection, the concentration over time (positive contrast) can be utilized to calculate dynamic diagnostic parameters like perfusion parameters in vessels and organs. Every acquired perfusion image thus requires a new bolus of tracer with a sufficiently large iron dose to be visible above the background. Main results. Perfusion parameters are calculated based on the time response of the proposed negative bolus and compared to a positive bolus. Results from phantom experiments show that normalized signals from positive and negative boli are concurrent and deviations of calculated perfusion maps are low. Significance. Our method opens up the possibility to increase the total monitoring time of a future patient by utilizing a positive-negative contrast sequence, while minimizing the iron dose per acquired image.Publicationtype: Journal ArticleScopus© Citations 1 12 25 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Development and characterization of modular mouse phantoms for end-to-end testing and training in radiobiology experimentsObjective. In radiation oncology, experiments are often carried out using mice as a model for in vivo research studies. Due to recent technological advances in the development of high-precision small-animal irradiation facilities, the importance of quality assurance for both dosimetry and imaging is increasing. Additive manufacturing (AM) offers the possibility to produce complex models from a three-dimensional data set and to build cost-effective phantoms that can easily be adapted to different purposes. The aim of this work was therefore to develop detailed anatomical mouse models for quality assurance and end-to-end testing of small-animal irradiation and imaging by means of AM. Approach. Two mouse phantom concepts were designed, constructed, and examined for this purpose. The first model includes cavities corresponding to the most important organs. The final solid model was constructed using AM in two separate parts that can be attached with a plug connection after filling these cavities with tissue-equivalent mixtures. Moreover, different radiation dosimeters can be placed in the lower part of the model. For the second concept, AM was used for building modules like the phantom outer shell and bones, so that different mixtures can be used as a filling, without modifying the phantom structure. Main results. CT as well as Micro-CT scans of both concepts showed an excellent quality and adequate image contrast, with material attenuation properties close to those of mouse tissues, apart from the current bone surrogates. Radiation dose measurements with radiochromic films were, with some exceptions in areas with larges bone volumes, in agreement with calculations within less than ±4%. Significance. AM shows great potential for the development of mouse models that are inexpensive, easy to adapt, and accurate, thus enabling their use for quality assurance in small-animal radiotherapy and imaging. The introduction of such 3D-printable mouse phantoms in the workflow could also significantly reduce the use of living animals for optimization and testing of new imaging and irradiation protocols.Publicationtype: Journal ArticleScopus© Citations 1 42 130 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Simultaneous imaging of widely differing particle concentrations in MPI: Problem statement and algorithmic proposal for improvement(2021-05-07); ; ; ; Magnetic particle imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system 'shadows' nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.Publicationtype: Journal Article52 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Design of a head coil for high resolution mouse brain perfusion imaging using magnetic particle imaging(2020-11-25); ; ; ; Magnetic particle imaging (MPI) is a novel and versatile imaging modality developing toward human application. When up-scaling to human size, the sensitivity of the systems naturally drops as the coil sensitivity depends on the bore diameter. Thus, new methods to push the sensitivity limit further have to be investigated to cope for this loss. In this paper a dedicated surface coil for mice is developed, improving the sensitivity in cerebral imaging applications. Similar to magnetic resonance imaging the developed surface coil improves the sensitivity due to the closer vicinity to the region of interest. With the developed surface coil presented in this work, it is possible to image tracer samples containing only 896 pgfe and detect even small vessels and anatomical structures within a wild type mouse model. As current sensitivity measures require a tracer system a new method for determining a sensitivity measure without this requirement is presented and verified to enable comparison between MPI receiver systems.Publicationtype: Journal Article81